Publications

Climate-Lab activity results into constant scientific publication activity in top-tier journals. Find here our latest publications (full list 2015-now at page bottom)

A Hydrological–Energy Balance Model to Assess Land Surface Temperature at the Urban Scale: The Case Study of Milano, ItalyThis study uses a water–energy balance model together with satellite and ground meteorological data to evaluate Surface Urban Heat Island, and the effects of urban greening in Milano, Italy. Running ...

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Now available online our new paper on Urban Heat Island in Milano ! Congrats Sonia and everybody !

Analysis of future climate variability under CMIP6 scenarios based on a downscaling method considering wet days in the upper Yangtze River basin, China - Theoretical and Applied ClimatologyAccording to recent studies, the past decade was the hottest on record, and climate change is accelerating. As part of the Yangtze River Basin, the largest river basin in China, the Upper Yangtze River Basin (UYRB) plays a crucial role as the primary source of hydropower. However, the UYRB is also one of the most climate-sensitive regions within the basin, making the impact of climate change on this area particularly critical. We downscaled CMIP6 GCMs’ outputs of precipitation (including wet/dry spells sequence correction), and temperature projections (2024–2100), under four typical Shared Socioeconomic Pathways (SSPs), and we pursued a trend analysis upon these potential future climate series. We found significant upward trends in temperature across all SSPs in August, but no significant trends in precipitation for the same month. Additionally, for SSP370 and SSP585, there are significant upward trends in temperature in December, while precipitation showed no significant trends during that month. This may result in drier winters than now, increased potential evapotranspiration, and reduced surface (snow) water storage, impacting water resources availability. Consecutive dry/wet days at station, and basin scale show spatial-temporal heterogeneity, but generally wet spells are longer, and dry spells shorten moving from South-East to North-West.

A multi-criteria analysis for Environmental Flow Assessment based on hydraulic modellingEnvironmental Flow Assessment is crucial, when assessing the impact of water withdrawal on riverine habitat. Still, standard methods to tackle such ex…

Modelling the effects of potential climate change on the dynamics of multi-species mountain pastures: A case study in Gran Paradiso National Park, ItalyPasture dynamics of Alpine areas are linked to the complex cryospheric hydrology of Alpine catchment and to the interspecies competition, which are in…

Statistical downscaling of GCMs wind speed data for trend analysis of future scenarios: a case study in the Lombardy region - Theoretical and Applied ClimatologyNear-surface wind speed is a key climatic variable, affecting many sectors, such as energy production, air pollution, and natural hazard. Lombardy region of Italy is among the European areas with lowest average wind speed, leading generally to low air quality and wind energy potential. However, it is also one of the most affected area by tornadoes in Italy. Here we investigate possible changes in wind circulation as due to prospective global warming. We analysed wind speed WS under future scenarios (SSP1-2.6 and SSP5-8.5) from six Global Climate Models (GCMs) until 2100, tuned against observed WS data. We employed a statistical downscaling method, namely Stochastic Time Random Cascade (STRC) to correct locally GCMs outputs. Three statistical tests, i.e. Linear Regression, Mann Kendall, Moving Window Average, were carried out to analyse future trends of: annual WS averages, 95th quantile (as an indicator of large WS), and the number of days of calm wind per year (NWC). The proposed STRC algorithm can successfully adjust the mean, standard deviation, and autocorrelation structure of the GCM outputs. No strong trends are found for the future. The chosen variables would all display non-stationarity, and the 95th percentile display a positive trend for most of the stations. Concerning NWC, notable discrepancies among GCMs are seen. The STRC algorithm can be used to successfully adjust GCMs outputs to reflect locally observed data and to then generate credible long-term scenarios for WSs as a tool for decision-making.

An algorithm to generate 2D bathymetry of an Alpine river for habitat suitability assessment.Here we present an original approach to generate 2D high detail riverbed based on a drone photogrammetric survey, and RTK bathymetry measurements for …

Morphological indexes to describe snow-cover patterns in a high-alpine area | Annals of Glaciology | Cambridge CoreMorphological indexes to describe snow-cover patterns in a high-alpine area

Environmental Flow Assessment using multiple criteria: A case study in the Kumbih river, West Sumatra (Indonesia)Water withdrawal from rivers is a key resource for agriculture, industry, and power generation. However, in order to maintain riverine ecosystem, with…

Ex-post assessment of climate and hydrological projections: reliability of CMPI6 outputs in Northern Italy - Theoretical and Applied ClimatologyThis paper presents a validation of outputs from some GCMs of the CMIP6 project when used to assess climate projection and hydrological flows at a catchment scale for the case study area of the Lombardy region (Northern Italy). The modeling chain consists of (i) a choice of climatic scenarios from 10 GCMs of the CMIP6, (ii) the application of a stochastic downscaling procedure to make projections usable at the local scale, and (iii) the use of a semi-distributed physically based hydrological model Poli-Hydro for the generation of hydrological scenarios. Data on observed precipitation and temperature were collected from automatic weather stations, and the hydrological budget of four target catchments within the study area was assessed using Poli-Hydro. An ex-post (back-casting) analysis was performed upon the control data series from the GCMs by comparing statistics of relevant climate variables and model-simulated discharges against observed counterparts during the historical period 2002–2014. Then, during 2015–2021, the goodness of projections was assessed using confidence intervals. Our results show that the accuracy of GCMs in representing regional climate is not always reflected in a credible evaluation of local hydrology. The validation of climate patterns provides somewhat poor results; thus, the interaction among climate and hydrology needs to be explored carefully to warrant the credibility of hydrological scenarios. Overall, the spatial and temporal consistency of GCM projections, as explored here climatically and hydrologically, provides a clue about their dependability for basin scale management.

Centenary (1930–2023) climate, and snow cover changes in the Western Alps of Italy. The Ossola valley - Climatic ChangeIn this paper, we study centennial trends of climate and snow cover within the Ossola valley, in the Western Italian Alps. We pursue different tests (Mann Kendall MK, bulk, and sequential/progressive MKprog, Linear Regression, also with change point detection, and moving window average MW) on two datasets, namely (i) dataset1, daily temperature, precipitation, snow depth for 9 stations in the area, during 1930–2018, and (ii) dataset2, snow depth and density, measured twice a month (from February 1st to June 1st) for 47 stations during 2007–2023. We also verify correlation with glacier retreat nearby. In dataset1, we highlight a positive trend for minimum temperature with MK, and Linear Regression. Using MKprog/MW, a negative change of snow cover depth, and duration starting from the late 1980s is found. In dataset2, despite the annual variability in snow cover and 2022–2023 winter drought, we assess the maximum snow water equivalent (SWE) to be delayed with respect to maximum snow depth at high altitude (over a month above 2.700 m a.s.l.), highlighting the effect of settling in decreasing snow depth during spring. We also present a formula linking through Linear Regression the Day of the Year of SWE peak to altitude, relevant to assess the onset of thaw season. Due to the high altitude of the stations, and the paradigmatic nature of the Ossola Valley, hosting Toce River, a main contributor to the Lake Maggiore of Italy, our results are of interest, and can be used as a benchmark for the Italian Alps.

Climate Change Effects upon Pasture in the Alps: The Case of Valtellina Valley, ItalyIn this study, we assessed the potential effects of climate change upon the productivity of mountain pastures in the Valtellina valley of Italy. Two species, Trisetum flavescens and Nardus stricta, among the most abundant in Italian pastures, were chosen for the simulation of low- and high-altitude pastures, respectively. We introduced some agroclimatic indices, related to growing season parameters, climate, and water availability, to evaluate the impacts of climate change upon pasture production. First, the dynamic of the pasture species was evaluated for the present period using the climate-driven, hydrologically based model Poli-Hydro, nesting the Poli-Pasture module simulating plants growth. Poli-Pasture was validated against yield data, at province scale, and at local scale. Then, agroclimatic indices were calculated. Subsequently, IPCC scenarios of the Fifth and Sixth Assessment Reports (AR5 and AR6) were used to project species production and agroclimatic indices until the end of the 21st century. In response to increased temperature under all scenarios, a large potential for an increased growing season length and species yield overall (between +30% and +180% for AR5 at 2100) was found. Potential for decreased yield (until −31% for AR5) is seen below 1100 m asl in response to heat stress; however, it is compensated by a large increase higher up (between +50% and +140% for AR5 above 2000 m asl). Larger evapotranspiration is foreseen and larger water demand expected. However, specific (for hectares of pasture) water use would decrease visibly, and no significant water limitations would be seen. Results provide preliminary evidence of potential livestock, and thereby economic development in the valley at higher altitudes than now.

Modeling snowmelt influence on shallow landslides in Tartano valley, Italian AlpsShallow landslides (SLs) are rapid debris flows slides, typically occurring in the mountain areas, involving the most superficial soil layers up to 5 …

Assessment of Recent Flow, and Calving Rate of the Perito Moreno Glacier Using LANDSAT and SENTINEL2 ImagesWe mapped flow velocity and calving rates of the iconic Perito Moreno Glacier (PMG), belonging to the Southern Patagonian Icefield (SPI) in the Argentinian Patagonia. We tracked PMG from 2001 to 2017, focusing mostly upon the latest images from 2016–2017. PMG delivers about ca. 106 m3 day−1 of ice in the Lago Argentino, and its front periodically reaches the Peninsula Magallanes. Therein, the PMG causes an ice-dam, clogging Brazo Rico channel, and lifting water level by about 10 m, until ice-dam failure, normally occurring in March. Here, we used 36 pairs of satellite images with a resolution of 10 m (SENTINEL2, visible, 9 pairs of images) and 15 m (LANDSAT imagery, panchromatic, 27 pairs of images) to calculate surface velocity (VS). We used Orientation Correlation technique, implemented via the ImGRAFT® TemplateMatch tool. Calving rates were then calculated with two methods, namely, (i) M1, by ice flow through the glacier front, and (ii) M2, by ice flow at 7.5 km upstream of the front minus ablation losses. Surface velocity ranged from about 4 m day−1 in the accumulation area to about 2 m day−1 in the calving front, but it is variable seasonally with maxima in the summer (December–January–February). Calving rate (CRM) ranges from 7.72 × 105 ± 32% to 8.76 × 105 ± 31% m3 day−1, in line with recent studies, also with maxima in the summer. We found slightly lower flow velocity and calving rates than previously published values, but our estimates cover a different period, and a generally large uncertainty in flow assessment suggests a recent overall stability of the glacier.

Physical Modeling of Snow Gliding: A Case Study in the NW Italian AlpsSnow gliding, a slow movement downhill of snow cover, is complex to forecast and model and yet is extremely important, because it drives snowpack dynamics in the pre-avalanching phase. Despite recent interest in this process and the development of some studies therein, this phenomenon is poorly understood and represents a major point of uncertainty for avalanche forecasting. This study presents a data-driven, physically based, time-dependent 1D model, Poli-Glide, able to predict the slow movement of snowpacks along a flow line at the daily scale. The objective of the work was to create a useful snow gliding model, requiring few, relatively easily available input data, by (i) modeling snowpack evolution from measured precipitation and air temperature, (ii) evaluating the rate and extent of movement of the snowpack in the gliding phase, and (iii) assessing fracture (i.e., avalanching) timing. Such a model could be then used to provide hazard assessment in areas subject to gliding, thereby, and subsequent avalanching. To do so, some simplifying assumptions were introduced, namely that (i) negligible traction stress occurs within soil, (ii) water percolation into snow occurs at a fixed rate, and (iii) the micro topography of soil is schematized according to a sinusoidal function in the absence of soil erosion. The proposed model was then applied to the “Torrent des Marais-Mont de La Saxe” site in Aosta Valley, monitored during the winters of 2010 and 2011, featuring different weather conditions. The results showed an acceptable capacity of the model to reproduce snowpack deformation patterns and the final snowpack’s displacement. Correlation analysis based upon observed glide rates further confirmed dependence against the chosen variables, thus witnessing the goodness of the model. The results could be a valuable starting point for future research aimed at including more complex parameterizations of the different processes that affect gliding.

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Most recent publications of Climate-Lab team (2015-2023)

1) Minora, U., D. Godone, S. Lorenzini, C. D’Agata, D. Bocchiola, G. S. Barcaza, C. Smiraglia, G. A. Diolaiuti, 2008–2011 snow cover area (SCA) variability over 18 watersheds of the Central Chile through MODIS data, Physical Geography and Quaternary Dynamics, GFDQ, 38(2), 169-174, 2015. http://gfdq.glaciologia.it/038_2_06_2015.

2) Viganò, G., Confortola, G., Fornaroli, R., Canobbio, S., Mezzanotte, V., Bocchiola D., Future climate change may affect habitat in Alpine streams: a case study in Italy, ASCE J. Hydrol. Eng., 10.1061/(ASCE)HE.1943-5584.0001293, 04015063, 21(2), 2016.

3) Bozza, A., Durand, A., Confortola, G., Allenbach, B., Bocchiola, D., Potential of remote sensing and open street data for flood mapping in poorly gauged areas: a case study in Gonaives, Haiti, Applied Geomatics, 8, 117-131, 2016. http://link.springer.com/article/10.1007/s12518-016-0171-x. ISI, SCOPUS

4) Senese, A., Maugeri, M., Ferrari, S., Confortola, G., Bocchiola, D., Diolaiuti, G., Modelling shortwave and longwave downward radiation and air temperature driving ablation at the Forni glacier (Stelvio national park, Italy), Physical Geography and Quaternary Dynamics, GFDQ, 39, 89-99, 2016.

5) Soncini A., Bocchiola, D., Confortola, G., Minora, U., Vuillermoz, E., Salerno, F., Viviano, G., Shrestha, D., Senese, A., Smiraglia, C., Diolaiuti, G., Future hydrological regimes and glacier cover in the Everest region: the case study of the Dudh Koshi basin, Science of the Total Environment STOTEN, 565, 1084-1101, 2016. http://www.sciencedirect.com/science/article/pii/S0048969716310683 IF 5-years: 4.32.

6) Soncini, A., Bocchiola, D., Azzoni, R.S., Diolaiuti, G., A methodology for monitoring and modeling of high altitude Alpine catchments, Progress in Physical Geography, 41, 4, 393-420, 2017. DOI: 10.1177/0309133317710832. Online first. http://journals.sagepub.com/doi/full/10.1177/0309133317710832, IF 5-years: 4.49.

7) Bocchiola, D., Agriculture and food security under climate change in Nepal: Mini-Review, Advances in Plants and Agriculture Research, 6(6), 00237, 2017. DOI: 10.15406/apar.2017.06.00237

8) Bocchiola, D., Soncini, A., Pasture modeling in mountain areas: the case of Italian Alps, and Pakistani Karakoram, Agricultural Research and Technology, 8(3): 555736, 1-8, 2017. DOI: 10.19080/ARTOAJ.2017.08.555736, 2017.

9) Bocchiola, D., Soncini, A., Pelosi, M.G., Effects of hydrological changes upon cooperation in transnational catchments: the case of Syr Darya. Water International, 42, 1-22, 2017. DOI: 10.1080/02508060.2017.1376568. IF 2016: 1.54. Latest Articles. http://www.tandfonline.com/doi/full/10.1080/02508060.2017.137656.

10) Aili, T., Soncini, A., Bianchi, A., Diolaiuti, G., D’Agata, C., Bocchiola, D., Assessing water resources under climate change in high-altitude catchments: a methodology and an application in the Italian Alps. Theoret. Appl. Climatol. 135, 135–-56, 2019.

11) https://doi.org/10.1007/s00704-017-2366-4, 1-22, 2018.

12) D’Agata, C., Soncini, A., Bocchiola, D., Maragno, D., Smiraglia, C., Diolaiuti, G. Recent area and volume loss of Alpine glaciers in the Adda River of Italy and their contribution to hydropower production, Cold Regions Science and Technology,14, 172-184, 2018.

13) Bocchiola, D., Soncini, A., Senese, A., Diolaiuti, G., Modelling hydrological components of the Rio Maipo of Chile, and their prospective evolution under climate change. Climate 6(3), 57, 2018. https://doi.org/10.3390/cli6030057.

14) Akbari, H., Soncini, A, Dinpashoh, Y., Fakheri-Fard, A., Bocchiola, D., Operation of two major reservoirs of Iran under IPCC scenarios during XXI Century, Hydrol. Process., 2018, 1-18. https://doi.org/10.1002/hyp.132

15) Baldasso, V., Soncini, A., Azzoni, R.S., Diolaiuti, G., Bocchiola, D., Recent evolution of glaciers in Western Asia in response to global warming: the case study of mount Ararat, Turkey, Theoret. Appl. Climatol., 10.1007/s00704-018-2581-7, 1-15.

16) Capolongo, D., Refice, A., Bocchiola D., D’Addabbo, A., Vouvalidis, K., Soncini, A., Stamatopulos, L., Coupling multitemporal remote sensing with geomorphology and hydrological modeling for post flood recovery in the Strymonas dammed river basin (Greece). Science of the total Environment, 651(2), 1958-1968.

17) Bocchiola, D., Galizzi, M., Bombelli, G. M., and Soncini, A.: Mapping snow avalanches hazard in poorly monitored areas. The case of Rigopiano avalanche, Apennines of Italy, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2018-358, in review, 2018.

18) Bocchiola, D., Brunetti, L., Soncini, A., Polinelli, F., Gianinetto, M., Impact of climate change on agricultural productivity and food security in the Himalayas: a case study in Nepal, Agricultural Systems, 171, 113-125, 2019.

19) Bombelli, G., Soncini, A., Bianchi, A., Bocchiola, D. Potentially modified hydropower production under climate change in the Italian Alps, Hydrol. Proc., 33(17), 2355-2372, https://onlinelibrary.wiley.com/doi/10.1002/hyp.13473.

20) Stucchi, L., Bombelli, G.M., Bianchi, A., Bocchiola, D., Hydropower potential of the Alpine cryosphere in the era of climate change. The case of a storage plant in Italy. Water, 11, 1599, 2019. doi:10.3390/w11081599.

21) Colombo, N., Bocchiola, D., Martin, M., Confortola, G., Salerno, F., Godone, D., D’Amico, M., Freppaz, M., High export of nitrogen and dissolved organic carbon from an Alpine glacier (Indren Glacier, NW Italian Alps)", Aquatic Sciences AQSC, 81:74, 1-13, 2019. DOI: 10.1007/s00027-019-0670-z.

22) Bombelli, G.M., Soncini, A., Bianchi, A., Bocchiola, D., Influence of climate change scenarios on energy price in the 21st century: a case study in Italy. Climate, 7(10), 121, 2019. doi:10.3390/cli7100121.

23) Gianinetto, M. Aiello, M., Polinelli, F., Frassy, F., Rulli, M.C., Ravazzani, G., Bocchiola, D., Chiarelli, D.D., Soncini, A., Vezzoli, R., D-RUSLE: a dynamic model to estimate potential soil erosion with satellite time series in the Italian Alps, European Journal of Remote Sensing (TEJR). DOI: 10.1080/22797254.2019.166949, 1-20, 2019.

24) Casale, F., Bombelli, G.M., Monti, R., Bocchiola, D., Hydro-power potential in the Kabul river of Afghanistan in the era of climate change, Theoretical and Applied Climatology, 139, 1415-1434, 2020.

25) Gianinetto, M., Aiello, M., Vezzoli, R., Polinelli, F.N., Rulli, M.C., Chiarelli, D.D., Bocchiola, D., Ravazzani, G., Soncini, A., Future Scenarios of Soil Erosion in the Alps under Climate Change and Land Cover Transformations Simulated with Automatic Machine Learning, Climate, 8, 28, 2020. doi:10.3390/cli8020028

26) Bocchiola, D., Bombelli, B.M., Camin, F., Ossi, P.M., Mass balance, and hydrology of Himalayan glaciers: a field study of the Khangri Nup (Khumbu, Everest), Water, 11, 433, 2020.

27) Mousavi, S.N., Júnior, R.S., Teixeira, E.D., Bocchiola, D., Nabipour, N., Mosavi, A., Shamshirband, S., Predictive Modeling the Free Hydraulic Jumps Pressure through Advanced Statistical Methods. Preprints, 2020. 2020010310 (doi: 10.20944/preprints202001.0310.v1). https://www.preprints.org/manuscript/202001.0310/v1

28) Mousavi, S.N., Júnior, R.S., Teixeira, E.D., Bocchiola, D., Nabipour, N., Mosavi, A., Shamshirband, S., Predictive Modeling the Free Hydraulic Jumps Pressure through Advanced Statistical Methods, Mathematics, 8(3), 323, 1-16, 2020. https://doi.org/10.3390/math8030323

29) Mousavi, S.N., Farsadizadeh, D., Salmasi, F., Hosseinzadeh Dalir, A., Bocchiola, D., Analysis of minimal and maximal pressures, uncertainty and spectral densityof fluctuating pressures beneath classical hydraulic jumps, Water Supply, 20, 1909-21, 2020.

30) Bocchiola, D. Manara, M., Mereu, M., Impact of prospective climate change on Run of River hydropower schemes in the Himalayas: the case study of the Dudh Koshi basin of Nepal. Water, 12(8): 2625, 2020.

31) Duratorre, T., Bombelli, G.M., Menduni, G., Bocchiola, D. Hydropower Potential in the Alps under Climate Change Scenarios. The Chavonne Plant, Val D'Aosta. Water, 12, 2021, 2020.

32) Vione, D. N. Colombo, D. Said-Pullicino, D. Bocchiola, G. Confortola, F. Salerno, G. Viviano, S. Fratianni, M. Martin, D. Godone, M. Freppaz, Seasonal variations in the optical characteristics of dissolved organic matter in glacial pond water, STOTEN, 759, 2021, 143464. https://doi.org/10.1016/j.scitotenv.2020.143464

33) Fuso, F., Casale, F. Giudici, F. Bocchiola, D., Future Hydrology of the Cryospheric Driven Lake Como Catchment in Italy under Climate Change Scenarios, Climate. 2021, 9(1), 8; https://doi.org/10.3390/cli9010008.

34) Stucchi, L., Bignami, D.F., Bocchiola, D., Del Curto, D., Garzulino, A., Rosso, R. Assessment of Climate-Driven Flood Risk and Adaptation Supporting the Conservation Management Plan of a Heritage Site. The National Art Schools of Cuba. Climate, 9(2), 23, 2021. https://doi.org/10.3390/cli9020023.

35) Bombelli, G.M., Tomiet, S., Bianchi, A., Bocchiola, D., Impact of Prospective Climate Change Scenarios upon Hydropower Potential of Ethiopia in GERD and GIBE Dams. Water 2021, 13(5), 716. https://doi.org/10.3390/w13050716

36) Maruffi, L., Stucchi, L., Casale, F., Bocchiola, D., Soil erosion and sediment transport under climate change for Mera River,in Italian Alps of Valchiavenna, STOTEN, 806, 150651, 2022.

37) Bombelli, G.M., Confortola, G., Maggioni, M., Freppaz, M., Bocchiola, D., Modelling of gliding avalanches: a case study in the North-Western Italian Alps, Climate, 9(12), 171; https://doi.org/10.3390/cli9120171, 2021.

38) Casale, F., Fuso, F., Giuliani, M., Castelletti, A., Bocchiola, D., Exploring future vulnerabilities of subalpine Italian regulated lakes under different climate scenarios: bottom‐up vs top-down and CMIP5 vs CMIP6, J. Hydrol: Reg. Studies, 38, 100973, 2021.

39) Bocchiola, D., Chirico, F., Senese, A., Azzoni, R. S., Diolaiuti, G.A., Assessment of recent flow, and calving rate of the Perito Moreno Glacier using remote sensing, and UAV data, Remote Sensing, 14(1), 52, 2022.

40) Carletti, F., Michel, A., Casale, F., Bocchiola, D., Lehning, M., Bavay, M., A comparison of hydrological models with different level of complexity in Alpine regions in the context of climate change, HESS, Hydrol. Earth Syst. Sci., 26, 3447–3475, 2022, https://doi.org/10.5194/hess-26-3447-2022.

41) Casale, F., Bocchiola, D. Climate Change Effects upon Pasture in the Alps: The Case of Valtellina Valley, Italy. Climate, 2022. https://www.mdpi.com/2225-1154/10/11/173

42) Stucchi, L., Fuso, L., Bocchiola, D., Bonacina, L., Fornaroli, R., Evaluation of water temperature under changing climate and its effect on river habitat in a regulated Alpine catchment. J. Hydrol., 616, 128816.

43) Chiarelli, D.D., Galizzi, M., Bocchiola, D., Rosso, R., Rulli, M.C., Modelling Snowmelt influence on shallow landslides in Tartano valley, Italian Alps, Science of The Total Environment, 856(1)158772.

44) Stucchi, L., Dresti, C., Bocchiola, D., Centenary (1930–2023) climate, and snow cover changes in the Western Alps of Italy. The Ossola valley, Climatic Change, 176(6), 1-24.

45) Stucchi L., Bocchiola D., Simoni, C., Ambrosini, S. R., Bianchi A., Rosso, R. Future hydropower production under the framework of NextGenerationEU: the case of Santa Giustina reservoir in Italian Alps, Renewable Energies, 215, 118980, 2023.

46) Stucchi L., Bocchiola D. Environmental Flow Assessment using multiple criteria: A case study in the Kumbih river, West Sumatra (Indonesia), Science of The Total Environment, 901, 166516, 2023.

47) Ferrarin, L., Schulz, K, Bocchiola, D., Koch, F., Morphological indexes to describe snow-cover patterns in a high-alpine area. Ann. Glaciology, 1-12, https://doi.org/10.1017/aog.2023.62, 2023.

48) Fuso, F., Bombelli, G., Bocchiola, D., Ex-post assessment of climate and hydrological projections. Reliability of CMPI6 outputs in Northern Italy, Theoretical and Applied Climatology, 16(1), 1-20, DOI: 10.1007/s00704-023-04698-5, 2023.

49) Stucchi, L., Sharifi, A., Fugazza, D., Traversa, G., Diolaiuti, G.A., Bocchiola, D. An algorithm to generate 2D riverbed bathymetry of an Alpine river for habitat suitability assessment. STOTEN, 918, 170703, 2024.

50) Ferrarin, L., Stucchi, L., Bocchiola, D., Statistical downscaling of GCMs wind speed data for trend analysis of future scenarios: a case study in the Lombardy region, TAC, https://doi.org/10.1007/s00704-024-04921-x, 2024.

51) Morgese, S., Casale, F., Movedi, E., Confalonieri, R., Bocchiola, D., Modelling the effects of potential climate change on the dynamics of multi-species mountain pastures: a case study in Gran Paradiso Park, Italy, Agricultural Systems, 217, 103942.

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